Collaborating using different object models

ABSTRACT

Systems and methods are provided for collaborating with different object models. Data corresponding to one or more source objects is received. The source objects is stored in a first object model, and each of the source objects is associated with information describing an entity. Matches between the respective information associated with the one or more source objects and respective information associated with one or more target objects are determined based on a query. The target objects are stored in a second object model. The one or more source objects are ranked based at least in part on the matches. A list of the ranked source objects are provided through an interface, the interface indicating a number of matching target objects for each of the source objects.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. Ser. No. 16/243,978, filedJan. 9, 2019, which is a continuation of U.S. Ser. No. 15/481,014, filedApr. 6, 2017, now U.S. Pat. No. 10,216,811, which claims the benefitunder 35 U.S.C. § 119(e) of U.S. Provisional Applications Ser. No.62/442,554, filed Jan. 5, 2017, the content of which is incorporated byreference in its entirety into the present disclosure

FIELD OF THE INVENTION

This disclosure relates to retrieving and presenting content.

BACKGROUND

Under conventional approaches, searching information of a group ofentities from a database poses great challenges. As the number of theentities increases, the burden for organizing searches and analysisbecomes significant.

SUMMARY

Various embodiments of the present disclosure can include systems,methods, and non-transitory computer readable media configured toperform collaborating with different object models. Data correspondingto one or more source objects is received. The source objects is storedin a first object model, and each of the source objects is associatedwith information describing an entity. Matches between the respectiveinformation associated with the one or more source objects andrespective information associated with one or more target objects aredetermined based on a query. The target objects are stored in a secondobject model. The one or more source objects are ranked based at leastin part on the matches. A list of the ranked source objects are providedthrough an interface, the interface indicating a number of matchingtarget objects for each of the source objects.

In some embodiments, the systems, methods, and non-transitory computerreadable media are configured to provide an option to categorize one ormore of the matched target objects in a folder associated with thecorresponding source object.

In some embodiments, the systems, methods, and non-transitory computerreadable media are configured to provide an option to resolve two ormore of the matched target objects into a single target object.

In some embodiments, the systems, methods, and non-transitory computerreadable media are configured to provide an option to resolve one of thesource objects and one of the target objects into a single targetobject.

In some embodiments, the source objects comprise one or more sourceperson objects.

In some embodiments, the target objects comprise at least one of aperson object or a data object.

In some embodiments, the query is based on personal informationassociated with one or more of the source objects.

In some embodiments, the query is a name search.

In some embodiments, the query is a personal identifier search.

In some embodiments, the query comprises one or more pieces of personalinformation associated with one of the source objects.

These and other features of the systems, methods, and non-transitorycomputer readable media disclosed herein, as well as the methods ofoperation and functions of the related elements of structure and thecombination of parts and economies of manufacture, will become moreapparent upon consideration of the following description and theappended claims with reference to the accompanying drawings, all ofwhich form a part of this specification, wherein like reference numeralsdesignate corresponding parts in the various figures. It is to beexpressly understood, however, that the drawings are for purposes ofillustration and description only and are not intended as a definitionof the limits of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

Certain features of various embodiments of the present technology areset forth with particularity in the appended claims. A betterunderstanding of the features and advantages of the technology will beobtained by reference to the following detailed description that setsforth illustrative embodiments, in which the principles of the inventionare utilized, and the accompanying drawings of which:

FIG. 1 illustrates an example environment for collaborating usingdifferent object models, in accordance with various embodiments.

FIG. 2 illustrates an example system for collaborating using differentobject models, in accordance with various embodiments.

FIGS. 3A-D illustrate example interfaces for collaborating usingdifferent object models, in accordance with various embodiments.

FIG. 4 illustrates a flowchart of an example method, in accordance withvarious embodiments.

FIG. 5 illustrates a block diagram of an example computer system inwhich any of the embodiments described herein may be implemented.

DETAILED DESCRIPTION

Some applications requiring extraction of database information regardinga group of entities may pose great challenges. For instance, a group ofproperty-defined objects can be provided for purposes of determiningmatches from one or more existing databases. Under conventionalapproaches, such entities may be searched individually or collectively.For example, a number of suspects and their basic information may beprovided to be matched against known culprits stored in a comprehensivedatabase. Each suspect and associated information may be received as asource object, while the database information may be stored as varioustarget objects. Conventionally, the suspect objects may be queried fromthe target objects, for example, using individual names or a commoncharacter shared by multiple suspects.

Such conventional approaches for information retrieval may not always beideal. Most applications typically require a systematic andcomprehensive search method that can render accurate and clear results,which becomes increasingly challenging when the received entities andthe database sizes scale up. As the number of the entities increases, sodoes the burden for performing searches. Even if the searches can becompleted, post-search organization is no less demanding to sort theresults in order. Further, since all received entity objects are treatedas a single item to search against the database, the returned searchresults are deficient in showing detailed corresponding relationsbetween each source object and each target object. Thus, it is desirableto provide a system for searching and analyzing objects in bulk.

A claimed solution rooted in computer technology overcomes problemsspecifically arising in the realm of computer technology. In variousembodiments, a computing system can be configured to receive datacorresponding to one or more entity objects that are stored in a firstobject model. Each entity object can be associated with informationdescribing some entity (e.g., a person, business, etc.). In someimplementations, a user accessing the computing system can compare theseentity objects against objects stored in a second object model. Forexample, the user may submit search queries to identify objects in thesecond object model that reference a first entity object in the firstobject model. These searches may involve matching information (e.g.,object properties) that is associated with the first source entityobject against respective information (e.g., object properties) that isassociated with objects in the second object model. In one example, thesearch query may be a user-defined rule referring to one or more objectproperties (e.g., name, passport number, etc.). In some implementations,the objects in the second object model may correspond to entities (e.g.,persons, businesses, etc.) and/or data (e.g., files, documents, databaseentries, and other forms of structured and/or unstructured data). Aftercompleting the search, the system may rank the received entity objectsbased on the number of matching objects in the second object model. Insome implementations, the user can select an option to categorize one ormore of the matching objects in a folder associated with the entityobject. This folder can be made accessible to other users of thecomputing system. The system may also provide an option to resolve twoor more objects into a single object.

FIG. 1 illustrates an example environment 100 for collaborating usingdifferent object models, in accordance with various embodiments. Asshown in FIG. 1, the example environment 100 can include at least onecomputing system 102 that includes one or more processors 104 and memory106. The memory 106 may be non-transitory and computer-readable. Thememory 106 may store instructions that, when executed by the one or moreprocessors 104, cause the one or more processors 104 to perform variousoperations described herein. The environment 100 may also include acomputing device 110 coupled to the system 102 and a data store 108 thatis accessible to the system 102. For example, the data store 108 mayinclude one or more searchable databases in which the objects are storedin a second object model. In some implementations, the objects in thesecond object model may correspond to entities (e.g., persons,businesses, etc.) and/or data (e.g., files, documents, database entries,etc.). An object model can store data as objects defined by objectcomponents, which can include properties (e.g., textual objectattributes such as names, emails, etc.), media (e.g., files, images,videos, binary data, etc.), notes (e.g., free text containers), and/orrelationships with other objects.

In some embodiments, the system 102 and the computing device 110 may beintegrated in a single device or system. Alternatively, the system 102and the computing device 110 may operate as separate devices, forexample, the computing device 110 may be a mobile device and the system102 may be a server. The data store 108 may be stored anywhereaccessible to the system 102, for example, in the memory 106, in anotherdevice coupled to the system 102, etc. Various operations of the system102 are described below in reference to FIG. 2 to FIG. 4.

FIG. 2 illustrates an example system 200 for collaborating usingdifferent object models, in accordance with various embodiments. Theoperations shown in FIG. 2 and presented below are intended to beillustrative.

In various embodiments, a user may operate a computing device 110 toinput (or provide) data describing one or more source objects 202 and aquery 204 to a system 102. The source objects 202 may be stored in afirst object model that is accessible to the computing device 110. Some,or all, of the sources objects may be associated with informationdescribing an entity (e.g., persons, businesses, etc.). The query 204may be a command (or operation) to search for objects stored indifferent object models that match any of the source objects 202. Insome embodiments, the query 204 may comprise one or more defined rules(e.g., property match rule, full text rule, name match rule, etc.)and/or filters (e.g., object type filter, property filter, date filter,etc.). For example, the property match rule may limit the query resultsto those matching one or more of the properties of the source objects,the full text rule may search the full text (or some portion of thetext) of the target objects that include one or more terms that matchterms included in text associated with the source objects, and the namematch rule may search one or more name properties of the target objectand one or more name properties of source objects for matches. Theobject type filter may limit the query results to target objects havinga pre-defined (or specified) object type (e.g., person objects only),the property filter may limit the query results to target objectsmatching a pre-defined (or specified) property, and the date filter maylimit the query results to target objects associated with a pre-defined(or specified) date and/or date period. Though this figure shows thatthe source objects 202 and the query 204 are transmitted from the samecomputing device, they can be sent from different devices. In someembodiments, the source objects 202 and/or the query 204 may besubmitted through a search interface that is provided by the system 102.The source objects 202 and/or the query 204 may be received by thesystem 102. In various embodiments, information sent and receivedbetween devices (e.g., the computing device 110, the system 102, etc.)can be transmitted over one or more computer networks (e.g., local areanetwork, the Internet, etc.).

The query may be performed (or executed) using at least one data store,such as the data store 108 storing target objects. The target objectscan be stored in a second object model. In some embodiments, the system102 can submit the query 206 to the data store 108, and the data store108 can provide the system 102 with one or more determined matches 208that are responsive to the query 206. For example, each of these searchresults 206 can reference an object in the data store 108 that isresponsive to one or more search terms included in the search query 206.The substance of the query 204 and the query 206 may be the same. Insome embodiments, when executing the query 206, the system 102 can beconfigured to search the data store 108 for objects that are responsiveto the query 206, and these objects can be organized into a set ofmatches 208.

In various embodiments, the system 102 may rank the one or more sourceobjects 202 based at least in part on the determined matches 208, andprovide a list of the ranked source objects through an interface. Theinterface may indicate a number of matching target objects for each ofthe source objects. The ranking may be based on relevance, time, etc.For example, the system 102 may render the source object with the mostnumber of matched target objects on top. As such, the source objects canbe searched in bulk against a set of target objects, and results can beprovided in an orderly manner. Various rule options and filter optionscan also be used to perform the search and refine the search results, asdescribed above. More details describing the collaboration usingdifferent object models are provided below in reference to FIGS. 3A-3D.

FIGS. 3A-3D respectively illustrate example interfaces 300, 310, 320,and 330 for collaborating using different object models, in accordancewith various embodiments. The description of FIGS. 3A-3D are intended tobe illustrative and may be modified in various ways according to theimplementation. The interfaces 300, 310, 320, and 330 may be provided bya computing system (e.g., the system 102) and accessed by a computingdevice (e.g., the computing device 110). In some embodiments, theinterfaces may be presented through a respective display screen of thecomputing device 110 and/or the system 102. In some embodiments, theinterfaces may be provided by a software application running on thecomputing device 110 and/or the system 102.

As shown in FIG. 3A, six source objects may be received by the system102 and shown in an imported objects interface 302. These source objectsare stored in a first object model. In this example, all six sourceobjects “John Smith,” “John Doe,” “Tom Jay,” “Henry Smith,” “HenryKing,” and “Chris Jay” are person objects. Alternatively, the sourceobjects may correspond to other types of entities such as business,organization, etc. Each source object can be associated withinformation. As shown here by selecting the “John Smith” object, itsassociated information is provided in an interface 304. For example, the“John Smith” object may be associated with the name “John Smith,” aportrait photo, “properties,” “media,” “links,” a passport number, anumber of name aliases, some travel history, and a number of images. The“properties” tab may link to the properties object component describedabove. Similarly, the “media” tab may link to the media object componentand the “relationships” tab may link to the relationships objectcomponent. The interface 300 is provided as an example and, depending onthe implementation, there may be many different ways to present theinformation. For example, the information may be presented in a tabularformat with the objects shown in rows and their properties shown incolumns.

In some embodiments, the user may submit search queries to identifyobjects in the second object model that reference a first entity objectin the first object model. These searches may involve matchinginformation that is associated with the first source entity objectagainst respective information that is associated with objects in thesecond object model. In one example, the search query may be auser-defined rule referring to one or more object properties (e.g.,name, passport number, etc.). As shown in FIG. 3A, a search option 306is provided to search (or evaluate) the source objects against thetarget objects. In some implementations, the target objects may bestored in the second object model and may correspond to entities (e.g.,persons, businesses, etc.) and/or data (e.g., files, documents, databaseentries, etc.). The user may also input or select one or more rulesand/or filters, as described above, to define the search. The rules maydefine searches based on one or more personal identifiers, such as anobject name, a name alias, a passport number, etc. For example, analias-alias search is described below in reference to FIG. 3B, and analias-full text search is described below in reference to FIG. 3D.

The alias-alias search may refer to searching for matches between one ormore source objects' aliases and one or more target objects' aliases.The alias may be one of the properties associated with the objects. Asshown in an interface 312 of FIG. 3B, after the search is complete, theresults may be ranked (here, only the top two matched objects areshown). For each object, the results can also indicate a number ofresults saved to a subject folder corresponding to the entity that isassociated with the object, and a number of results marked not relevant.The number of results in the subject folder of a source object shows anumber of target objects associated with the source object.

After the alias-alias search is performed, the matched target objectsmay be rendered. For example, as shown in an interface 314 of FIG. 3B,three of fourteen matched target objects are provided. Each targetobject is also provided with options to mark as “not relevant” or to“add to folder.” Further, as shown in an interface 316 of FIG. 3B,matched source objects and target objects can be provided forside-by-side comparison. In this example, the “Louis L.” target object315 is selected to compare with the “John Smith” source object 313. Insome embodiments, after comparing the matched objects, if the userthinks the matched target object is not related to the source object,the user may mark the target object as irrelevant by selecting an option317. Otherwise, if the user thinks the matched target object isimportant, the user may select an option 319 to add the target object toa folder associated with the source object for further investigation oranalysis. As such, a user accessing the system 102 and/or the computingdevice 110 can easily compare the source objects stored in the firstobject model against the target objects stored in a second object model.Such comparisons allow for matching between related objects that arestored in different object models, thereby facilitating investigationsusing data stored in different object models and/or platforms.

FIG. 3C illustrates an option to resolve two or more objects that a userhas determined to be similar or related. FIG. 3C is mostly similar toFIG. 3B, except that the “John S.” target object 325 has been selectedinstead of the “Louis L.” target object 323. By comparing the sourceobject “John Smith” 321 and the matched target object “John S.” 325 inan interface 322, a user may determine that these two objects correspondto the same person. Once such determination is made, the user may selectthe trigger button 324 which causes the system 102 to resolve these twoobjects. That is, the two objects may be joined (or merged) as oneobject by merging their properties, media, links, photos, etc. to obtaina consolidated object with consolidated properties, media, links,photos, etc. The consolidated object may be used to replace the originalsource object (e.g., object 321) and/or the original matched targetobject (e.g., object 325). In some embodiments, information describingthe resolved object and/or changes to the source object may becommunicated back to the sender of the source object.

The alias-full text search may refer to searching for matches betweenone or more aliases of source objects and text (e.g., portions of text,full text, etc.) associated with target objects. The full text mayinclude aliases and other properties, as well as files, documents, andlinks that are associated with the target objects. As shown in aninterface 332 of FIG. 3D, after the search is complete, the results maybe ranked. The ranking may be based on the number of matching targetobjects in the second object model. For example, object “John Smith” isranked first because the object 331 has the most number of matches(e.g., 899). As shown in an interface 334 of FIG. 3D, matched targetobjects are provided. For example, a first matching target object 333 isa document that includes terms that are responsive to an aliascorresponding to the object 331. Similarly, a second matching targetobject 335 which is also a document that includes terms that responsiveto an alias corresponding to the object 331 is also shown in theinterface 334. In some embodiments, matched key words can be highlightedin the target objects. As described above, the user may input or selectone or more rules and/or filters to define the search for the matchingtarget objects. In this example, the search was defined in the rules toinclude target objects that contain the source object's first and lastname within two words as match results. Thus, both “John Smith” and“John AB Smith” in the text of the target object 333 are determined asmatches to “John Smith” of the source object 331. As shown in aninterface 336 of FIG. 3D, details of a selected matched object can beshown for further analysis or investigation. In some implementations,the user can select an option to categorize one or more of the matchingobjects in a subject folder associated with the source object (e.g., bymarking “add to folder” in the interface 334 or 336) or an option tolabel the matching objects as being irrelevant (e.g., by marking “notrelevant” in the interface 334 or 336). This folder can be madeaccessible to other users of the system 102 and/or the computing device110 (e.g., the sender of the source object, collaborators, etc.).Similar to resolving the source object and the matched target objectdescribed above, two or more matched target objects may also be resolvedinto a single target object. For example, one of the matched targetobjects, including its properties, media, links, photos, and otherassociated information, may be moved to merge with the other matchedtarget object.

FIG. 4 illustrates a flowchart of an example method 400, according tovarious embodiments of the present disclosure. The method 400 may beimplemented in various environments including, for example, theenvironment 100 of FIG. 1. The operations of method 400 presented beloware intended to be illustrative. Depending on the implementation, theexample method 400 may include additional, fewer, or alternative stepsperformed in various orders or in parallel. The example method 400 maybe implemented in various computing systems or devices including one ormore processors.

At block 402, data corresponding to one or more source objects isreceived. The source objects can be stored in a first object model, andeach of the source objects can be associated with information describingan entity. At block 404, matches between the respective informationassociated with the one or more source objects and respectiveinformation associated with one or more target objects are determinedbased on a query. The target objects are stored in a second objectmodel. At block 406, the one or more source objects are ranked based atleast in part on the matches. At block 408, a list of the ranked sourceobjects are provided through an interface, the interface indicating anumber of matching target objects for each of the source objects.

Hardware Implementation

The techniques described herein are implemented by one or morespecial-purpose computing devices. The special-purpose computing devicesmay be hard-wired to perform the techniques, or may include circuitry ordigital electronic devices such as one or more application-specificintegrated circuits (ASICs) or field programmable gate arrays (FPGAs)that are persistently programmed to perform the techniques, or mayinclude one or more hardware processors programmed to perform thetechniques pursuant to program instructions in firmware, memory, otherstorage, or a combination. Such special-purpose computing devices mayalso combine custom hard-wired logic, ASICs, or FPGAs with customprogramming to accomplish the techniques. The special-purpose computingdevices may be desktop computer systems, server computer systems,portable computer systems, handheld devices, networking devices or anyother device or combination of devices that incorporate hard-wiredand/or program logic to implement the techniques.

Computing device(s) are generally controlled and coordinated byoperating system software, such as iOS, Android, Chrome OS, Windows XP,Windows Vista, Windows 7, Windows 8, Windows Server, Windows CE, Unix,Linux, SunOS, Solaris, iOS, Blackberry OS, VxWorks, or other compatibleoperating systems. In other embodiments, the computing device may becontrolled by a proprietary operating system. Conventional operatingsystems control and schedule computer processes for execution, performmemory management, provide file system, networking, I/O services, andprovide a user interface functionality, such as a graphical userinterface (“GUI”), among other things.

FIG. 5 is a block diagram that illustrates a computer system 500 uponwhich any of the embodiments described herein may be implemented. Thecomputer system 500 includes a bus 502 or other communication mechanismfor communicating information, one or more hardware processors 504coupled with bus 502 for processing information. Hardware processor(s)504 may be, for example, one or more general purpose microprocessors.

The computer system 500 also includes a main memory 506, such as arandom access memory (RAM), cache and/or other dynamic storage devices,coupled to bus 502 for storing information and instructions to beexecuted by processor 504. Main memory 506 also may be used for storingtemporary variables or other intermediate information during executionof instructions to be executed by processor 504. Such instructions, whenstored in storage media accessible to processor 504, render computersystem 500 into a special-purpose machine that is customized to performthe operations specified in the instructions.

The computer system 500 further includes a read only memory (ROM) 508 orother static storage device coupled to bus 502 for storing staticinformation and instructions for processor 504. A storage device 510,such as a magnetic disk, optical disk, or USB thumb drive (Flash drive),etc., is provided and coupled to bus 502 for storing information andinstructions.

The computer system 500 may be coupled via bus 502 to a display 512,such as a cathode ray tube (CRT) or LCD display (or touch screen), fordisplaying information to a computer user. An input device 514,including alphanumeric and other keys, is coupled to bus 502 forcommunicating information and command selections to processor 504.Another type of user input device is cursor control 516, such as amouse, a trackball, or cursor direction keys for communicating directioninformation and command selections to processor 504 and for controllingcursor movement on display 512. This input device typically has twodegrees of freedom in two axes, a first axis (e.g., x) and a second axis(e.g., y), that allows the device to specify positions in a plane. Insome embodiments, the same direction information and command selectionsas cursor control may be implemented via receiving touches on a touchscreen without a cursor.

The computing system 500 may include a user interface module toimplement a GUI that may be stored in a mass storage device asexecutable software codes that are executed by the computing device(s).This and other modules may include, by way of example, components, suchas software components, object-oriented software components, classcomponents and task components, processes, functions, attributes,procedures, subroutines, segments of program code, drivers, firmware,microcode, circuitry, data, databases, data structures, tables, arrays,and variables.

In general, the word “module,” as used herein, refers to logic embodiedin hardware or firmware, or to a collection of software instructions,possibly having entry and exit points, written in a programminglanguage, such as, for example, Java, C or C++. A software module may becompiled and linked into an executable program, installed in a dynamiclink library, or may be written in an interpreted programming languagesuch as, for example, BASIC, Perl, or Python. It will be appreciatedthat software modules may be callable from other modules or fromthemselves, and/or may be invoked in response to detected events orinterrupts. Software modules configured for execution on computingdevices may be provided on a computer readable medium, such as a compactdisc, digital video disc, flash drive, magnetic disc, or any othertangible medium, or as a digital download (and may be originally storedin a compressed or installable format that requires installation,decompression or decryption prior to execution). Such software code maybe stored, partially or fully, on a memory device of the executingcomputing device, for execution by the computing device. Softwareinstructions may be embedded in firmware, such as an EPROM. It will befurther appreciated that hardware modules may be comprised of connectedlogic units, such as gates and flip-flops, and/or may be comprised ofprogrammable units, such as programmable gate arrays or processors. Themodules or computing device functionality described herein arepreferably implemented as software modules, but may be represented inhardware or firmware. Generally, the modules described herein refer tological modules that may be combined with other modules or divided intosub-modules despite their physical organization or storage.

The computer system 500 may implement the techniques described hereinusing customized hard-wired logic, one or more ASICs or FPGAs, firmwareand/or program logic which in combination with the computer systemcauses or programs computer system 500 to be a special-purpose machine.According to one embodiment, the techniques herein are performed bycomputer system 500 in response to processor(s) 504 executing one ormore sequences of one or more instructions contained in main memory 506.Such instructions may be read into main memory 506 from another storagemedium, such as storage device 510. Execution of the sequences ofinstructions contained in main memory 506 causes processor(s) 504 toperform the process steps described herein. In alternative embodiments,hard-wired circuitry may be used in place of or in combination withsoftware instructions.

The term “non-transitory media,” and similar terms, as used hereinrefers to any media that store data and/or instructions that cause amachine to operate in a specific fashion. Such non-transitory media maycomprise non-volatile media and/or volatile media. Non-volatile mediaincludes, for example, optical or magnetic disks, such as storage device510. Volatile media includes dynamic memory, such as main memory 506.Common forms of non-transitory media include, for example, a floppydisk, a flexible disk, hard disk, solid state drive, magnetic tape, orany other magnetic data storage medium, a CD-ROM, any other optical datastorage medium, any physical medium with patterns of holes, a RAM, aPROM, and EPROM, a FLASH-EPROM, NVRAM, any other memory chip orcartridge, and networked versions of the same.

Non-transitory media is distinct from but may be used in conjunctionwith transmission media. Transmission media participates in transferringinformation between non-transitory media. For example, transmissionmedia includes coaxial cables, copper wire and fiber optics, includingthe wires that comprise bus 502. Transmission media can also take theform of acoustic or light waves, such as those generated duringradio-wave and infra-red data communications.

Various forms of media may be involved in carrying one or more sequencesof one or more instructions to processor 504 for execution. For example,the instructions may initially be carried on a magnetic disk or solidstate drive of a remote computer. The remote computer can load theinstructions into its dynamic memory and send the instructions over atelephone line using a modem. A modem local to computer system 500 canreceive the data on the telephone line and use an infra-red transmitterto convert the data to an infra-red signal. An infra-red detector canreceive the data carried in the infra-red signal and appropriatecircuitry can place the data on bus 502. Bus 502 carries the data tomain memory 506, from which processor 504 retrieves and executes theinstructions. The instructions received by main memory 506 may retrievesand executes the instructions. The instructions received by main memory506 may optionally be stored on storage device 510 either before orafter execution by processor 504.

The computer system 500 also includes a communication interface 518coupled to bus 502. Communication interface 518 provides a two-way datacommunication coupling to one or more network links that are connectedto one or more local networks. For example, communication interface 518may be an integrated services digital network (ISDN) card, cable modem,satellite modem, or a modem to provide a data communication connectionto a corresponding type of telephone line. As another example,communication interface 518 may be a local area network (LAN) card toprovide a data communication connection to a compatible LAN (or WANcomponent to communicated with a WAN). Wireless links may also beimplemented. In any such implementation, communication interface 518sends and receives electrical, electromagnetic or optical signals thatcarry digital data streams representing various types of information.

A network link typically provides data communication through one or morenetworks to other data devices. For example, a network link may providea connection through local network to a host computer or to dataequipment operated by an Internet Service Provider (ISP). The ISP inturn provides data communication services through the world wide packetdata communication network now commonly referred to as the “Internet”.Local network and Internet both use electrical, electromagnetic oroptical signals that carry digital data streams. The signals through thevarious networks and the signals on network link and throughcommunication interface 518, which carry the digital data to and fromcomputer system 500, are example forms of transmission media.

The computer system 500 can send messages and receive data, includingprogram code, through the network(s), network link and communicationinterface 518. In the Internet example, a server might transmit arequested code for an application program through the Internet, the ISP,the local network and the communication interface 518.

The received code may be executed by processor 504 as it is received,and/or stored in storage device 510, or other non-volatile storage forlater execution.

Each of the processes, methods, and algorithms described in thepreceding sections may be embodied in, and fully or partially automatedby, code modules executed by one or more computer systems or computerprocessors comprising computer hardware. The processes and algorithmsmay be implemented partially or wholly in application-specificcircuitry.

The various features and processes described above may be usedindependently of one another, or may be combined in various ways. Allpossible combinations and sub-combinations are intended to fall withinthe scope of this disclosure. In addition, certain method or processblocks may be omitted in some implementations. The methods and processesdescribed herein are also not limited to any particular sequence, andthe blocks or states relating thereto can be performed in othersequences that are appropriate. For example, described blocks or statesmay be performed in an order other than that specifically disclosed, ormultiple blocks or states may be combined in a single block or state.The example blocks or states may be performed in serial, in parallel, orin some other manner. Blocks or states may be added to or removed fromthe disclosed example embodiments. The example systems and componentsdescribed herein may be configured differently than described. Forexample, elements may be added to, removed from, or rearranged comparedto the disclosed example embodiments.

Conditional language, such as, among others, “can,” “could,” “might,” or“may,” unless specifically stated otherwise, or otherwise understoodwithin the context as used, is generally intended to convey that certainembodiments include, while other embodiments do not include, certainfeatures, elements and/or steps. Thus, such conditional language is notgenerally intended to imply that features, elements and/or steps are inany way required for one or more embodiments or that one or moreembodiments necessarily include logic for deciding, with or without userinput or prompting, whether these features, elements and/or steps areincluded or are to be performed in any particular embodiment.

Any process descriptions, elements, or blocks in the flow diagramsdescribed herein and/or depicted in the attached figures should beunderstood as potentially representing modules, segments, or portions ofcode which include one or more executable instructions for implementingspecific logical functions or steps in the process. Alternateimplementations are included within the scope of the embodimentsdescribed herein in which elements or functions may be deleted, executedout of order from that shown or discussed, including substantiallyconcurrently or in reverse order, depending on the functionalityinvolved, as would be understood by those skilled in the art.

It should be emphasized that many variations and modifications may bemade to the above-described embodiments, the elements of which are to beunderstood as being among other acceptable examples. All suchmodifications and variations are intended to be included herein withinthe scope of this disclosure. The foregoing description details certainembodiments of the invention. It will be appreciated, however, that nomatter how detailed the foregoing appears in text, the invention can bepracticed in many ways. As is also stated above, it should be noted thatthe use of particular terminology when describing certain features oraspects of the invention should not be taken to imply that theterminology is being re-defined herein to be restricted to including anyspecific characteristics of the features or aspects of the inventionwith which that terminology is associated. The scope of the inventionshould therefore be construed in accordance with the appended claims andany equivalents thereof.

Engines, Components, and Logic

Certain embodiments are described herein as including logic or a numberof components, engines, or mechanisms. Engines may constitute eithersoftware engines (e.g., code embodied on a machine-readable medium) orhardware engines. A “hardware engine” is a tangible unit capable ofperforming certain operations and may be configured or arranged in acertain physical manner. In various example embodiments, one or morecomputer systems (e.g., a standalone computer system, a client computersystem, or a server computer system) or one or more hardware engines ofa computer system (e.g., a processor or a group of processors) may beconfigured by software (e.g., an application or application portion) asa hardware engine that operates to perform certain operations asdescribed herein.

In some embodiments, a hardware engine may be implemented mechanically,electronically, or any suitable combination thereof. For example, ahardware engine may include dedicated circuitry or logic that ispermanently configured to perform certain operations. For example, ahardware engine may be a special-purpose processor, such as aField-Programmable Gate Array (FPGA) or an Application SpecificIntegrated Circuit (ASIC). A hardware engine may also includeprogrammable logic or circuitry that is temporarily configured bysoftware to perform certain operations. For example, a hardware enginemay include software executed by a general-purpose processor or otherprogrammable processor. Once configured by such software, hardwareengines become specific machines (or specific components of a machine)uniquely tailored to perform the configured functions and are no longergeneral-purpose processors. It will be appreciated that the decision toimplement a hardware engine mechanically, in dedicated and permanentlyconfigured circuitry, or in temporarily configured circuitry (e.g.,configured by software) may be driven by cost and time considerations.

Accordingly, the phrase “hardware engine” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. As used herein,“hardware-implemented engine” refers to a hardware engine. Consideringembodiments in which hardware engines are temporarily configured (e.g.,programmed), each of the hardware engines need not be configured orinstantiated at any one instance in time. For example, where a hardwareengine comprises a general-purpose processor configured by software tobecome a special-purpose processor, the general-purpose processor may beconfigured as respectively different special-purpose processors (e.g.,comprising different hardware engines) at different times. Softwareaccordingly configures a particular processor or processors, forexample, to constitute a particular hardware engine at one instance oftime and to constitute a different hardware engine at a differentinstance of time.

Hardware engines can provide information to, and receive informationfrom, other hardware engines. Accordingly, the described hardwareengines may be regarded as being communicatively coupled. Where multiplehardware engines exist contemporaneously, communications may be achievedthrough signal transmission (e.g., over appropriate circuits and buses)between or among two or more of the hardware engines. In embodiments inwhich multiple hardware engines are configured or instantiated atdifferent times, communications between such hardware engines may beachieved, for example, through the storage and retrieval of informationin memory structures to which the multiple hardware engines have access.For example, one hardware engine may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware engine may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware engines may also initiate communications with input oroutput devices, and can operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented enginesthat operate to perform one or more operations or functions describedherein. As used herein, “processor-implemented engine” refers to ahardware engine implemented using one or more processors.

Similarly, the methods described herein may be at least partiallyprocessor-implemented, with a particular processor or processors beingan example of hardware. For example, at least some of the operations ofa method may be performed by one or more processors orprocessor-implemented engines. Moreover, the one or more processors mayalso operate to support performance of the relevant operations in a“cloud computing” environment or as a “software as a service” (SaaS).For example, at least some of the operations may be performed by a groupof computers (as examples of machines including processors), with theseoperations being accessible via a network (e.g., the Internet) and viaone or more appropriate interfaces (e.g., an Application ProgramInterface (API)).

The performance of certain of the operations may be distributed amongthe processors, not only residing within a single machine, but deployedacross a number of machines. In some example embodiments, the processorsor processor-implemented engines may be located in a single geographiclocation (e.g., within a home environment, an office environment, or aserver farm). In other example embodiments, the processors orprocessor-implemented engines may be distributed across a number ofgeographic locations.

Language

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Although an overview of the subject matter has been described withreference to specific example embodiments, various modifications andchanges may be made to these embodiments without departing from thebroader scope of embodiments of the present disclosure. Such embodimentsof the subject matter may be referred to herein, individually orcollectively, by the term “invention” merely for convenience and withoutintending to voluntarily limit the scope of this application to anysingle disclosure or concept if more than one is, in fact, disclosed.

The embodiments illustrated herein are described in sufficient detail toenable those skilled in the art to practice the teachings disclosed.Other embodiments may be used and derived therefrom, such thatstructural and logical substitutions and changes may be made withoutdeparting from the scope of this disclosure. The Detailed Description,therefore, is not to be taken in a limiting sense, and the scope ofvarious embodiments is defined only by the appended claims, along withthe full range of equivalents to which such claims are entitled.

It will be appreciated that an “engine,” “system,” “data store,” and/or“database” may comprise software, hardware, firmware, and/or circuitry.In one example, one or more software programs comprising instructionscapable of being executable by a processor may perform one or more ofthe functions of the engines, data stores, databases, or systemsdescribed herein. In another example, circuitry may perform the same orsimilar functions. Alternative embodiments may comprise more, less, orfunctionally equivalent engines, systems, data stores, or databases, andstill be within the scope of present embodiments. For example, thefunctionality of the various systems, engines, data stores, and/ordatabases may be combined or divided differently.

“Open source” software is defined herein to be source code that allowsdistribution as source code as well as compiled form, with awell-publicized and indexed means of obtaining the source, optionallywith a license that allows modifications and derived works.

The data stores described herein may be any suitable structure (e.g., anactive database, a relational database, a self-referential database, atable, a matrix, an array, a flat file, a documented-oriented storagesystem, a non-relational No-SQL system, and the like), and may becloud-based or otherwise.

As used herein, the term “or” may be construed in either an inclusive orexclusive sense. Moreover, plural instances may be provided forresources, operations, or structures described herein as a singleinstance. Additionally, boundaries between various resources,operations, engines, engines, and data stores are somewhat arbitrary,and particular operations are illustrated in a context of specificillustrative configurations. Other allocations of functionality areenvisioned and may fall within a scope of various embodiments of thepresent disclosure. In general, structures and functionality presentedas separate resources in the example configurations may be implementedas a combined structure or resource. Similarly, structures andfunctionality presented as a single resource may be implemented asseparate resources. These and other variations, modifications,additions, and improvements fall within a scope of embodiments of thepresent disclosure as represented by the appended claims. Thespecification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense.

Conditional language, such as, among others, “can,” “could,” “might,” or“may,” unless specifically stated otherwise, or otherwise understoodwithin the context as used, is generally intended to convey that certainembodiments include, while other embodiments do not include, certainfeatures, elements and/or steps. Thus, such conditional language is notgenerally intended to imply that features, elements and/or steps are inany way required for one or more embodiments or that one or moreembodiments necessarily include logic for deciding, with or without userinput or prompting, whether these features, elements and/or steps areincluded or are to be performed in any particular embodiment.

Although the invention has been described in detail for the purpose ofillustration based on what is currently considered to be the mostpractical and preferred implementations, it is to be understood thatsuch detail is solely for that purpose and that the invention is notlimited to the disclosed implementations, but, on the contrary, isintended to cover modifications and equivalent arrangements that arewithin the spirit and scope of the appended claims. For example, it isto be understood that the present invention contemplates that, to theextent possible, one or more features of any embodiment can be combinedwith one or more features of any other embodiment.

1. A system comprising: one or more processors; and a memory storing oneor more databases and instructions that, when executed by the one ormore processors, cause the system to perform: retrieving a source objectstored in a first object model and associated with an entity, the sourceobject comprising an attribute, a file, an image, or a video; conductinga search query based on an identity, the attribute, the file, the image,or the video of the source object and corresponding to a target object,the target object comprising a second attribute, a second file, a secondimage, or a second video; identifying that an alias for the sourceobject corresponds to the target object based on a match betweenrespective attributes, files, images or videos of the target object andof the alias of the source object, wherein the alias for the sourceobject comprises a common term with the source object and a second termabsent from the source object; and in response to identifying the alias,consolidating the alias for the source object and the source object tocreate a consolidated data object.
 2. The system of claim 1, wherein theinstructions further cause the system to perform: providing an option tocategorize the alias for the target object in a folder associated withthe source object.
 3. The system of claim 1, wherein the instructionsfurther cause the system to perform: merging a file, document, or linkthat is associated with the alias of the source object with the sourceobject.
 4. The system of claim 3, wherein the file, document, or linkcomprises terms that match the alias of the source object.
 5. The systemof claim 1, wherein the instructions further cause the system toperform: removing the target object and the source object and replacingthe target object and the source object with the consolidated dataobject.
 6. The system of claim 1, wherein the instructions further causethe system to perform: providing an option to resolve the informationassociated with the target object with the information associated withthe source object.
 7. The system of claim 1, wherein the search query isan alias search query comprising a portion of text associated with atleast one of files, documents, or links associated with the targetobject.
 8. The system of claim 1, wherein the source object comprises asource person object and comprises the attribute, the file, the image,and the video.
 9. The system of claim 1, wherein the target objectcomprises a person object or a data object.
 10. The system of claim 1,wherein the search query is based on identifying information associatedwith the source object.
 11. A method being implemented by a computingsystem including one or more physical processors and a storage mediastoring machine-readable instructions, the method comprising: retrievinga source object stored in a first object model and associated with anentity, the source object comprising an attribute, a file, an image, ora video; conducting a search query based on an identity, the attribute,the file, the image, or the video of the source object and correspondingto a target object, the target object comprising a second attribute, asecond file, a second image, or a second video; identifying that analias for the source object corresponds to the target object based on amatch between respective attributes, files, images or videos of thetarget object and of the alias of the source object, wherein the aliasfor the source object comprises a common term with the source object anda second term absent from the source object; and in response toidentifying the alias, consolidating the alias for the source object andthe source object to create a consolidated data object.
 12. The methodof claim 11, further comprising providing an option to categorize thealias for the target object in a folder associated with the sourceobject.
 13. The method of claim 11, further comprising merging a file,document, or link that is associated with the alias of the source objectwith the source object.
 14. The method of claim 13, wherein the file,document, or link comprises terms that match the alias of the sourceobject.
 15. The method of claim 11, further comprising removing thetarget object and the source object and replacing the target object andthe source object with the consolidated data object.
 16. The method ofclaim 11, further comprising providing an option to resolve theinformation associated with the target object with the informationassociated with the source object.
 17. The method of claim 11, whereinthe search query is an alias search query comprising a portion of textassociated with at least one of files, documents, or links associatedwith the target object.
 18. The method of claim 11, wherein the sourceobject comprises a source person object and comprises the attribute, thefile, the image, and the video.
 19. The method of claim 11, wherein thetarget object comprises a person object or a data object.
 20. The methodof claim 11, wherein the search query is based on identifyinginformation associated with the source object.